Wellbore Skin Effect Calculation using Temperature Measurements

ABSTRACT

Methods and system to calculate a skin effect using wellbore temperature measurements are described herein. In a generalized method, data corresponding to wellbore characteristics, reservoir characteristics, and a preliminary pressure drop around a wellbore due to a Joule-Thomson (“J-T”) effect are obtained downhole. The data is then input into a wellbore fluid temperature model and/or a reservoir fluid temperature model to calculate a wellbore fluid temperature profile and/or reservoir fluid temperature profile, respectively. The calculated wellbore and/or reservoir fluid temperature profiles may be calibrated using fluid temperatures measurements in the wellbore. The calibration may involve comparing the calculated temperature profiles to the measured temperature profiles to ensure the difference between the two profiles does not exceed an error threshold.

FIELD OF THE DISCLOSURE

The present disclosure relates generally to hydrocarbon exploration and, more specifically, to the calculation of wellbore skin effect using wellbore temperature measurements.

BACKGROUND

Pressure transient testing has long been a proven technique to estimate the additional pressure drop resulting from damage around the near wellbore region (also referred to as “skin”). Most conventional approaches to skin determination have revolved around pressure measurements only. However, often times, it is not possible to obtain pressure transient data owing to costs and/or safety reasons.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a schematic of a wellbore/reservoir system configuration, according to certain illustrative methods of the present disclosure;

FIG. 2 plots a sample distribution of flowing fluid temperature in the reservoir at different production rates, according to certain illustrative methods of the present disclosure;

FIGS. 3 and 4 are flow charts of alternate methods of determining skin effect, according to illustrative methods of the present disclosure;

FIG. 5 shows a formation testing system, according to certain illustrative embodiments of the present disclosure; and

FIG. 6 illustrates a formation testing system for drilling operations according to an illustrative embodiment of the present disclosure.

DESCRIPTION OF ILLUSTRATIVE EMBODIMENTS

Illustrative embodiments and related methods of the present disclosure are described below as they might be employed in a downhole method to determine the skin effect around a wellbore using temperature measurements. In the interest of clarity, not all features of an actual implementation or method are described in this specification. It will of course be appreciated that in the development of any such actual embodiment, numerous implementation-specific decisions must be made to achieve the developers' specific goals, such as compliance with system-related and business-related constraints, which will vary from one implementation to another. Moreover, it will be appreciated that such a development effort might be complex and time-consuming, but would nevertheless be a routine undertaking for those of ordinary skill in the art having the benefit of this disclosure. Further aspects and advantages of the various embodiments and related methods of the disclosure will become apparent from consideration of the following description and drawings.

As described herein, illustrative embodiments and methods of the present disclosure provide a method and system to calculate skin effect using wellbore temperature measurements. In a generalized method, data corresponding to wellbore characteristics, reservoir characteristics, and a preliminary pressure drop around a wellbore due to a heating or cooling effect (e.g., Joule-Thomson (“J-T”) effect) are obtained downhole. The data is then input into a wellbore fluid temperature model and/or a reservoir fluid temperature model to calculate a wellbore fluid temperature profile and/or reservoir fluid temperature profile, respectively. The calculated wellbore and/or reservoir fluid temperature profiles may be calibrated using actual fluid temperatures measurements in the wellbore. The calibration may involve comparing the calculated temperature profiles to the measured temperature profiles to ensure the difference between the two profiles does not exceed some defined error threshold.

If there is a deviation exceeding the threshold, the preliminary pressure drop that is input into the wellbore and/or reservoir fluid temperature models is changed to once again calculate the wellbore and reservoir fluid temperature profiles. When the difference between the calculated and measured fluid temperature profiles falls within the defined error threshold, the corresponding pressure drop due to the J-T effect is output by the system as the final pressure drop, wherein the final pressure drop is used to calculate the skin effect along the wellbore.

An alternative method may include the use of a formation tester. The formation test string includes the use of a pump, the heat from which may give rise to temperature. Knowing this heat quantity may allow deduction of the contribution of the pump in raising the temperature and enable calculation of the pressure drop that is responsible for the remaining increase in temperature. Thereby skin effect can be estimated from this pressure drop.

Accordingly, the present disclosure provides a method to determine skin without the need to perform conventional pressure transient testing. Pressure transient testing has long been a technique used to estimate the additional pressure drop (referred to as “skin effect” or “ΔP”) resulting from damage around the near wellbore region (also referred to as “skin”). However often times, it is not possible to obtain pressure transient data owing to costs and/or safety reasons.

Therefore, in illustrative methods the present disclosure, by using a combination of pressure and temperature measurements in the wellbore and analytical temperature calculations in the reservoir, the additional pressure drop attributed to damage near the wellbore is calculated. The methods described herein make this possible by accounting for Joule-Thomson (J-T) heating/cooling of the fluid as it travels through the reservoir and enters the wellbore, among other heat transfer mechanisms. The cooling/heating phenomena of the J-T effect refers to the change in temperature observed when a gas expands while flowing through a restriction without any heat entering or leaving the system. The change may be positive or negative. For each gas, there is an inversion point that depends on temperature and pressure, below which it is cooled and above which it is heated. For example, for methane at 100° C. [212° F.], the inversion point occurs at about 500 atmospheres [7350 psi]. The magnitude of the change of temperature with pressure depends on the J-T coefficient for a particular gas. Thus, the J-T effect often causes a temperature decrease as gas flows through pores of a reservoir to the wellbore.

In one approach of the present disclosure to determine the skin effect, the present disclosure accounts for the J-T effect during production. In an alternative approach, a formation tester is used to gather the pressure and temperature information, and the heat generated by the pump is calculated and deducted from the temperature increase in the surrounding formation due to flow and damage.

The present disclosure uses models along with wellbore measurements to provide methods to calculate skin damage in a well. The methods require an analytical temperature model for wellbore and/or the reservoir. The analytical reservoir model includes a comprehensive energy balance equation that takes into account energy change in the system due to temperature and pressure transients, conductive and convective heat transport, J-T heating/cooling and heat transfer across the system boundary. Similarly, the analytical wellbore temperature model includes energy balance for the wellbore fluid and the reservoir to calculate wellbore fluid temperature. In both these models, fluid temperature is dependent upon the pressure in the system, which forms the cornerstone of the present disclosure.

As will be described in more detail below, the illustrative methods require the formation/reservoir parameters and fluid pressure-volume-temperature (“PVT”) data. Once the reservoir model has all the desired data inputs, a theoretical radial temperature profile of the reservoir is calculated. In the same manner, using the wellbore completion information and the fluid PVT data, a temperature profile in the wellbore is calculated. Both these temperature profiles are dependent on pressure change. By comparing the calculated fluid temperatures in the wellbore/reservoir with the measured fluid temperatures in the wellbore and using that to calibrate the wellbore/reservoir temperature fluid temperature models, the pressure change leading to J-T heating/cooling during the drawdown can be determined. Thereafter, the pressure change may be used to determine skin.

FIG. 1 illustrates a simplified wellbore/reservoir system configuration forming the basis of the reservoir and wellbore fluid temperature models, according to certain illustrative methods of the present disclosure. With reference to FIG. 1, the reservoir system considered is a 1D radial reservoir where fluid flow occurs only in the radial direction. The only flowing fluid in the reservoir is oil, and there is no free gas in the system. Connate water remains immobile. Note the fluid flow in the idealized circular reservoir occurs in the “negative r direction.

A principle for estimation of fluid-temperature distribution in the reservoir is conservation of energy in the system, which includes reservoir fluid and rock. Conservation of mass for reservoir fluids is also incorporated to achieve a comprehensive energy-balance equation of the system. The model also assumes the reservoir is perfectly horizontal; thus, gravitational effects (change in fluid potential energy) are negligible.

The general form of thermal energy balance in terms of equation of change for internal energy can be written as:

$\begin{matrix} {{{\frac{\partial}{\partial t}\rho \; \hat{U}} = {{- \left( {{\nabla{\cdot \rho}}\; \hat{U}\overset{\rightharpoonup}{u}} \right)} - \left( {\nabla{\cdot \overset{\rightharpoonup}{q}}} \right) - {p\left( {\nabla{\cdot \overset{\rightharpoonup}{u}}} \right)} - \left( {\overset{\rightharpoonup}{\tau}\text{:}{\nabla\overset{\rightharpoonup}{u}}} \right) + \overset{.}{Q}}},} & {{Eq}.\mspace{14mu} (1)} \end{matrix}$

where Û is fluid internal energy, p is fluid and/or rock density, and {right arrow over (u)} is fluid local velocity. The ∇·term generally represents the net input rate of energy per unit volume of the system. The first term on the left side of Equation 1 represents the total rate of internal energy increase in the system. The first and second terms on the right side are net input rate of internal energy of the system caused by convective transport and heat conduction, respectively. The third term represents the net reversible rate of internal energy increase due to fluid compression (pressure difference), while the fourth term is the net irreversible rate of internal energy increase caused by fluid viscous dissipation. The fourth term may also referred to as the “J-T,” “frictional,” or “viscous dissipation” term.

In addition to heat conduction, convection, and the J-T effect caused by fluid flow in the reservoir, energy transfer from surroundings (over- and under-burden formation) to the system (reservoir fluids and formation) is considered. Therefore, a term representing the net energy transfer rate between the system and surroundings, {dot over (Q)}, is added to the energy-balance equation as the last term in Equation 1.

By using principles of rock and fluid enthalpy, Fourier's law of conduction, Newton's law of cooling, conservation of mass, and Darcy's law, Equation 1 can be rearranged and rewritten as:

$\begin{matrix} {{{\left\lbrack {{\varnothing \; s_{o}\rho_{o}c_{po}} + {\varnothing \; s_{w}\rho_{w}c_{pw}} + {\left( {1 - \varnothing} \right)\rho_{f}c_{pf}}} \right\rbrack \frac{\partial T}{\partial t}} + {\rho_{o}u_{r}c_{po}\frac{\partial T}{\partial r}} + {\rho_{o}u_{r}\sigma_{o}\frac{\partial p}{\partial r}} + {\left\lbrack {{\varnothing \; s_{o}\rho_{o}\sigma_{o}} + {\varnothing \; s_{w}\rho_{w}\sigma_{w}} - 1} \right\rbrack \frac{\partial p}{\partial t}}} = {{\frac{1}{r}{\frac{\partial}{\partial r}\left\lbrack {\lambda \; r\frac{\partial T}{\partial r}} \right\rbrack}} + \overset{.}{Q}}} & {{Eq}.\mspace{14mu} (2)} \end{matrix}$

Equation 2 is considered a comprehensive energy-balance equation for our system. The first term on the left side of Equation 2 contains the heat capacity of oil, water, and rock, which collectively represents energy change due to temperature transients. Similarly, the second term represents convective heat transport. The third term is energy change due to the J-T effect, and the fourth term represents energy change due to pressure transients in the reservoir. The first term on the right side is energy change from radial heat conduction, and the last term represents rate of heat transfer across the system boundary (to over- and under-burden formations).

The wellbore and reservoir fluid temperature models described herein contain certain assumptions. The reservoir is assumed to homogeneous and the rock and fluid properties are considered time invariant. Other general assumptions include: the only flowing fluid in the reservoir is oil; the reservoir is producing at a constant rate; the original temperature of over- and under-burden formation is the same as the reservoir temperature at initial conditions. The elevation differences from reservoir depth are negligible; over- and under-burden formations are infinite sources/sinks. Over- and under-burden formations remain at their original temperatures even after heat transfer to/from the reservoir occurs; radial heat conduction is negligible during constant rate production; the pressure transient term,

$\frac{\partial p}{\partial t},$

is assumed to be negligible. Thus, for a given flow rate, pressure varies in the radial direction, but not with time; fluid temperature and pressure remain constant at the reservoir boundary; porosity and permeability remain unchanged; the fluid's local velocity (superficial velocity) can be estimated from Darcy's equation:

$\begin{matrix} {q = {{{- \frac{kA}{\mu}}\frac{\partial p}{\partial r}} = {{- \frac{2\pi \; {rhk}}{\mu}}\frac{\partial p}{\partial r}\mspace{14mu} {and}}}} & {{Eq}.\mspace{14mu} (3)} \\ {u_{r} = {\frac{q}{A} = {\frac{q}{2\pi \; {rh}} = {{- \frac{k}{\mu}}\frac{\partial p}{\partial r}}}}} & {{Eq}.\mspace{14mu} (4)} \end{matrix}$

Many of these assumptions are necessary to obtain a useful analytical solution to the problem.

To develop the analytical model, the comprehensive energy-balance equation of the system is rearranged by applying all the assumptions described above. The energy-balance equation can be reduced to the first-order, partial-differential equation (“PDE”):

$\begin{matrix} {{\frac{\partial T}{\partial t} - {\frac{B}{Ar}\frac{\partial T}{\partial r}} - \frac{C}{{Ar}^{2}}} = {{{- \frac{D}{A}}T} + {\frac{E}{A}.}}} & {{Eq}.\mspace{14mu} (5)} \end{matrix}$

The method of characteristics was used to solve the PDE to arrive at a final form of the analytical solution (reservoir model), which is given as:

$\begin{matrix} {{{T\left( {r,t} \right)} = {T_{i} + {\frac{C}{2B}e^{\frac{H({{Ar}^{2} + {2{Bt}}})}{2B}}{{Ei}\left\lbrack {- \frac{H\left( {{Ar}^{2} + {2{Bt}}} \right)}{2B}} \right\rbrack}} - {\frac{C}{2B}e^{\frac{{HAr}^{2}}{2B}}{{Ei}\left\lbrack {- \frac{{HAr}^{2}}{2B}} \right\rbrack}}}},} & {{Eq}.\mspace{14mu} (6)} \end{matrix}$

where T is fluid temperature; r is radius; t is time; T_(i) is the initial reservoir temperature; with A being defined as:

$\begin{matrix} {{A = {\left\lbrack {{\varnothing \; s_{o}p_{o}c_{po}} + {\varnothing \; s_{w}\rho_{w}c_{pw}} + {\left( {1 - \varnothing} \right)\rho_{f}c_{pf}}} \right\rbrack \left( \frac{2\pi \; h}{q} \right)}},} & {{Eq}.\mspace{14mu} (7)} \end{matrix}$

where ϕ is porosity; S_(o) is oil saturation; ρ_(w) is water density; S_(w) is water saturation; c_(pw) is water specific heat capacity; c_(pf) is formation specific heat capacity; ρ_(f) is formation density; and q is volumetric flow rate; and h is formation thickness.

$\begin{matrix} {{B = {\rho_{o}c_{po}}},} & {{Eq}.\mspace{14mu} (8)} \\ {{C = \frac{q\; \rho_{o}\sigma_{o}\mu}{2\pi \; {hk}}},} & {{Eq}.\mspace{14mu} (9)} \\ {{D = \frac{4h_{c}\pi}{q}},} & {{Eq}.\mspace{14mu} (10)} \\ {{E = {\frac{4h_{c}\pi}{q}T_{i}}},{and}} & {{Eq}.\mspace{14mu} (11)} \\ {H = {\frac{D}{A}.}} & {{Eq}.\mspace{14mu} (12)} \end{matrix}$

With regard to the wellbore fluid temperature model of the present disclosure, when production is initiated or when the production rate is changed, thermal transients are set in that take a much longer time to stabilize than its pressure counterpart. The flow rate becomes stable soon after its initiation or change from one rate to another. However, temperature changes for the corresponding period take a much longer time to attain stability. The expression for transient flowing fluid temperature may be expressed as:

$\begin{matrix} {{T_{f_{n}} = {T_{{ei}_{n}} + {\frac{1 - e^{{({z - L})}L_{R}}}{L_{R}}\left( {{g_{G}\sin \; \theta} + \Phi + \frac{g\; \sin \; \theta}{{Jg}_{c}C_{p}}} \right)\left( {1 - e^{{- a}\; \Delta \; t}} \right)} + {\left( {T_{f_{n - 1}} - T_{{ei}_{n - 1}}} \right)e^{{- a}\; \Delta \; t}}}},} & {{Eq}.\mspace{14mu} (13)} \end{matrix}$

where T_(ei) is the earth or formation temperature; z is the variable wellbore depth from the surface, L is the total wellbore measured depth; L_(R) is the lumped relaxation parameter; g_(G) is the geothermal gradient; J represents appropriate conversion factors; and C_(p) is the specific heat capacity of the fluid.

$\begin{matrix} {{L_{R} = {\frac{2\pi}{C_{p}w}\left\lbrack \frac{r_{to}U_{t}k_{e}}{k_{e} + \left( {r_{to}U_{t}T_{D}} \right)} \right\rbrack}},} & {{Eq}.\mspace{14mu} (14)} \end{matrix}$

where w is the mass rate; r_(t) is tubing radius; k_(e) is thermal conductivity of formation; U_(t) is overall heat transfer coefficient; and T_(D) is dimensionless temperature. The lumped parameter Φ is defined as:

$\begin{matrix} {\Phi = {{\frac{v}{C_{p}{Jg}_{c}}\frac{dv}{dz}} - {144C_{J}\frac{dp}{dz}}}} & {{Eq}.\mspace{14mu} (15)} \end{matrix}$

where v is fluid velocity; C_(J) is the J-T coefficient; and

$\frac{dp}{dz}$

is ΔP. A more detailed discussion of the illustrative wellbore and reservoir fluid temperature models can be found in Estimating reliable gas rate with transient-temperature modeling for interpreting early-time cleanup data during transient testing, G. M. Hashmi et al., Journal of Petroleum Science and Engineering, Jun. 23, 2015, and Transient Flowing-Fluid Temperature Modeling in Oil Reservoirs for Flow Associated with Large Drawdowns, N. Chevarunotai et al., SPE-175008-MS, September 2015.

FIG. 2 plots a sample distribution of flowing-fluid temperature in a reservoir, according to certain illustrative methods of the present disclosure. In this example, the flowing-fluid temperature distribution is calculated using the methods described herein, producing at five different constant rates: 970, 2,050, 3270, 4,650, and 6,200 STB/D. As can be seen, the temperature near the wellbore may be different from the reservoir temperature. Therefore, the difference in temperature can help to determine skin, as described herein.

In view of the foregoing, FIG. 3 is a flow chart of a method to determine the skin effect around a wellbore, according to certain illustrative methods of the present disclosure. At block 302, wellbore fluid temperature, pressure and flow rate data is acquired by the system using a variety of means. For example, in method 300, downhole sensors may be utilized instead of a formation tester. However, in other methods, a formation tester, drill stem tester, or logging string may be utilized. Nevertheless, in addition to fluid temperature, pressure and flow rate data, a ΔP (i.e., pressure drop caused by skin damage around the wellbore) due to the J-T effect is acquired by the system. Initially, the ΔP is preliminary because it may be assumed as a random value or based upon a calculated guess (e.g., a skin effect of 2 or 5 would correspond to a certain pressure drop due to damage and thus with an expectant skin effect, the pressure drop could be initially assumed). Thereafter, as will be described in more detail below, subsequent ΔP values will be based on a comparison of calculated temperature profiles and measured temperature profiles.

At block 304, the data from block 302 is input into a reservoir and wellbore transient fluid temperature model, as described herein. At block 306, wellbore fluid and formation/reservoir properties are also input into the reservoir and wellbore transient fluid temperature models. The data at block 306 may include, for example, PVT data from labs, offset wells, etc. At block 308, wellbore and completion characteristic data are input into the reservoir and wellbore transient fluid models. The wellbore and completion characteristic data may include, for example, tubing diameter, casing diameter, length of well, inclination, type of completion, etc.

At block 310, the data obtained at blocks 302, 306 and 308 are input into the reservoir and wellbore transient fluid temperature models to calculate a wellbore fluid temperature profile and a reservoir fluid temperature profile. The wellbore fluid temperature profile models fluid temperatures along the wellbore, while the reservoir fluid temperature profile models fluid temperatures throughout the reservoir. At block 312, calibration of the reservoir and wellbore transient fluid temperature model is performed. To do so, actual measurements of the wellbore fluid temperature are acquired along the wellbore using downhole sensors, at block 314. In certain illustrative methods, the reservoir fluid temperature is also acquired by using the fluid temperature at the bottom of the wellbore, thereby also allowing calibration of the calculated reservoir fluid temperature profile at block 312.

At block 312, the system then compares the measured fluid temperature profiles (block 314) with the calculated fluid temperature profile of the wellbore (block 310). Here, the following may be used:

(T_(calc)−T_(meas))²  Eq.(16)

where T_(calc) is the calculated wellbore or reservoir fluid temperature(s), while T_(meas) is the measured wellbore or reservoir fluid temperature(s). At block 312, the system applies this equation to determine if the difference between the calculated and measured fluid temperatures is at a minimum in a given zone along the wellbore. Here, the minimum may be defined by a threshold such as, for example, within 5 or 10% of the T_(meas). In other examples, the threshold may be defined by the sensitivity of the downhole sensors (e.g., a minimum deviation of a 10^(th) of a degree from T_(meas)).

If, at block 312, the system determines that T_(calc) is not at a minimum in the zone, the system then assumes a new ΔP due to the J-T effect. The system may intelligently determine if the ΔP needs to be increased or decreased based upon the outcome at block 312. Alternatively, an error minimization technique may be applied in order to determine the new ΔP. In addition to the new ΔP, the system may also generate other assumed parameters (e.g. formation parameters) from the measured wellbore data (e.g., pressure and flow rate information). The newly determined parameters are then fed back into block 302, where the method begins again. However, if at block 312 the system determines that the difference between T_(calc) and T_(meas) is within the threshold, the system then determines if there are further producing zones to be analyzed at block 316. This determination may be made based upon, for example, the wellbore and completion characteristics. If further zones are to be analyzed, the system iteratively loops back to block 302 where the method 300 begins again. However, if no further zones are remaining, the system then outputs the calculated ΔP at block 318 (also referred to herein as the “final pressure drop” or “final ΔP”).

The ΔP of block 318 may then be used for a variety of purposes. For example, ΔP may be used to calculate skin using the following equation:

$\begin{matrix} {s = \frac{{kh}\; \Delta \; P}{141.2{qB}\; \mu}} & {{Eq}.\mspace{14mu} (17)} \end{matrix}$

Where s denotes the skin effect; k is the permeability in md; h is the reservoir thickness in ft; q is the flow rate in b/d; B is the formation volume factor; and μ is the fluid viscosity in cp.

The skin may then be used to determine the skin effect, which is useful in production analysis and estimates for revenue forecasting. In addition, the ΔP may be used to analyze the effectiveness of stimulation treatments or whether stimulation is necessary at all. There are many other applications of the ΔP, as will be understood by those ordinarily skilled in the art having the benefit of this disclosure.

FIG. 4 is a flow chart of another method for determining skin effect, according to an alternative method of the present disclosure. In method 400, unlike method 300 which uses downhole sensors, a formation tester (e.g., drill stem tester, production or logging string, etc.) is used. Accordingly, at block 402, the formation tester is deployed downhole at a desired depth and pumping (into or out of formation) is initiated. At block 404, fluid pressure and flow rate data including a first assumed ΔP due to the J-T effect is acquired and calculated by the system. At block 406, the system then inputs this data into a wellbore transient fluid temperature model (in this illustrative method, a reservoir model is not utilized). In addition, fluid and formation/reservoir properties are input into the wellbore model at block 408. Also, at block 410, the heat contribution of the formation tester pump is also input the model, as this must be taken into account for accurate modeling. Lastly, the wellbore and completion characteristics are also input into the wellbore model at block 412.

Thereafter, at block 414, the system used the wellbore transient fluid temperature model to calculate the fluid temperature profile along the wellbore. At block 416, the calculated fluid temperature profile is then calibrated using the measured fluid temperature profile (measured using the formation tester at block 418). If the difference between the calibrated and measured wellbore fluid temperature profiles is not within the threshold, the system assumes a second ΔP due to the J-T effect (and/or other parameter(s)) and iteratively loops back to block 404 to begin the method once more.

If, however, at block 416, the system determines the difference between the calculated and measured wellbore fluid temperatures is within the defined threshold, the system then determines if more zones need to be analyzed at block 420. If there are more zones, the system proceeds to the next zone and loops back to block 404 to begin again. If the system determines there are no more zones, then the ΔP is output as the final ΔP at block 422.

Now that illustrative methods have been described, an illustrative system to apply the method will now be described. FIG. 5 shows a formation testing system 510, according to certain illustrative embodiments of the present disclosure. Formation testing system 510 includes a downhole formation testing tool 520 conveyed in a wellbore 521 by a wireline 523 for testing and retrieving formation fluids from a desired selected formation 524 within the wellbore 521, according to the normal operation of the formation testing system 510. In addition to fluid testing, formation testing tool 520 also conducts fracturing of formation 524 and injects proppant into those induced fractures. Formation testing tool 520 contains a number of serially coupled modules, each module designed to perform a particular function. The type of modules and their order is changeable based on the design needs.

In the illustrative embodiment of FIG. 5, formation testing tool 520 includes a sequential arrangement of a fluid pumping section (“FPS”) module 540, a fluid testing module 531, compartment 527 containing a pressurized tank 525 and proppant slurry housing 529, packer/probe module 528 having an electro-hydraulic system (not shown), pressure gauge 566, a fluid testing module 532, FPS module 535, and a sample collection module 534, which is comprised of any number of sample chambers (not shown). Tool 520 also contains a control section 538 that contains downhole electronic circuitry for controlling the various modules of tool 520, as well as handling two-way telemetry for control communications from master control unit 590.

In addition, tool 520 can have incorporated into its modular design any number of packer elements, four shown and designated as 599 a, b, c, d. These packer elements are cylindrically shaped and designed so that when activated either by the injection of hydraulic fluid or by some mechanical means, they will expand in the radial direction and serve to make a hydraulic seal between the tool 520 and the formation. In practice, they can be deployed individually, or in pairs, or all simultaneously and serve to isolate parts of tool 520 from the adjoining wellbore in order to perform some specific well test operation.

Tool 520 is conveyed in wellbore 521 by the wireline 523 which contains conductors for carrying power to the various components of tool 520 and conductors or cables (coaxial or fiber optic cables) for providing two-way data communication between tool 520 and master control unit 590, which is placed uphole (on the surface) in a suitable truck 595 for land operations and in a cabin (not shown) for offshore operations, for example. Wireline 523 is conveyed by a drawworks 593 via a system of pulleys 522 a and 522 b.

Control unit 590 contains a computer and associated memory for storing therein desired programs and models. Control system 590 controls the operation of tool 520 and processes data received from tool 520 during operations to perform the methods described herein. Control unit 590 has a variety of associated peripherals, such as a recorder 592 for recording data and a display or monitor 594 for displaying desired information. The use of control unit 590, display 594 and recorder 592 is known in the art of well logging and is, thus, not explained in greater detail herein.

Still referring to the illustrative embodiment of FIG. 5, FPS module 540 performs pumping operations for formation testing tool 520. In this example, FPS module 540 includes a precision pump, which depending on the pump selection, can produce drawdowns in excess of 10000 psi below hydrostratic. Fluid testing module 531 forms part of FPS module 540 to analyze fluid during clean out of the reservoir.

Packer section 528 contains one or more packers/pads, such as 542 a and 542 b respectively, associated with probes 544 a and 544 b. When pressed hard against the formation, these packer/pads create a tight seal between the probes 544 a and 544 b so as to direct and only allow the flow of fluids from the probes into the reservoir, and from the reservoir through the probes and into the tool. During operations, packer/pads 542 a and 542 b are urged against a desired formation, such as reservoir 524, by urging hydraulically activated rams 546 a and 546 b, positioned opposite to 542 a and 542 b, against wellbore wall 521 a. An electro-hydraulic section (not shown) is housed in packer section 528, and includes a hydraulic pump for actuating probes 544 a and 544 b. Packer/pads 542 a and 542 b provide a seal to their respective probes 544 a and 544 b which embed into formation 524. Probes 544 a and 544 b are, among others, in fluid communication with compartment 527.

The electro-hydraulic pump of packer section 528 can also deploy hydraulic rams 546 a and 546 b, which causes packers 542 a and 542 b to urge against the wellbore wall 521 a. The system urges packers/pads 542 a and 542 b until a seal is formed between the packers/pads and wellbore wall 521 a to ensure that there is a proper fluid communication between wellbore formation 524 and probes 544 a and 544 b. In alternative embodiments, any other suitable means may also be used for deploying packers/pads 542 a and 542 b for the purposes of this disclosure. Probes 544 a and 544 b radially extend away from the tool body and penetrate into formation 524 when packers/pads 542 a and 542 b are urged against the wellbore interior wall 521 a. Packer/pad section 528 also contains temperature and pressure gauges (not shown) to monitor temperature and pressure changes during fluid sample collection process respectively from probes 544 a and 544 b to thereby perform the illustrative methods described herein.

FPS module 535, and various other valves, etc., control the formation fluid flow from the formation 524 into a flow line 550 via probes 544 a and 544 b during sampling. The pump operation is preferably controlled by control unit 590 or by a control circuit 538 located in tool 520. The fluid from probes 544 a and 544 b flows through flow line 550 and may be discharged into the wellbore via a port 552. A fluid control device, such as control valve, may be connected to the flow line for controlling the fluid flow from flow line 550 into the wellbore 521.

Pressure gauge 566 is used to determine the static and flowing formation pressure. This gives the operator an idea of what production rates to expect and to help them better calculate surface facilities. Fluid testing module 532 contains a fluid testing device which analyzes the fluid flowing through flow line 550. For the purpose of this disclosure, any suitable device or devices may be utilized to analyze the fluid. A number of different devices have been used to determine certain downhole parameters relating to the formation fluid and the contents (oil, gas, water and solids) of the fluid. Such information includes, for example, the drawdown pressure of fluid being withdrawn, fluid density and temperature, and fluid composition. Sample collection module 534 contains at least one fluid collection chamber for collecting the formation fluid samples. Although not shown, sample collection module also includes a fluid control device to allow fluid communication between the sample collection module 534 and the wellbore 521 as desired. FPS module 535 is used to pump fluid past the fluid testing module 532 and into sample collection module 534 during sampling.

FIG. 6 illustrates a formation testing system 600 for drilling operations according to an illustrative embodiment of the present disclosure. It should be noted that formation testing system 600 can also include a system for pumping or other operations. Formation testing system 600 includes a drilling rig 602 located at a surface 604 of a wellbore. Drilling rig 602 provides support for a down hole apparatus, including a drill string 608. Drill string 608 penetrates a rotary table 610 for drilling a borehole/wellbore 612 through subsurface formations 614. Drill string 608 includes a Kelly 616 (in the upper portion), a drill pipe 618 and a bottom hole assembly 620 (located at the lower portion of drill pipe 618). In certain illustrative embodiments, bottom hole assembly 620 may include drill collars 622, a downhole tool 624 and a drill bit 626. Downhole tool 624 may be any of a number of different types of tools including measurement-while-drilling (“MWD”) tools, logging-while-drilling (“LWD”) tools, etc.

During drilling operations, drill string 608 (including Kelly 616, drill pipe 618 and bottom hole assembly 620) may be rotated by rotary table 610. In addition or alternative to such rotation, bottom hole assembly 620 may also be rotated by a motor that is downhole. Drill collars 622 may be used to add weight to drill bit 626. Drill collars 622 also optionally stiffen bottom hole assembly 620 allowing it to transfer the weight to drill bit 626. The weight provided by drill collars 622 also assists drill bit 626 in the penetration of surface 604 and subsurface formations 614.

During drilling operations, a mud pump 632 optionally pumps drilling fluid (e.g., drilling mud), from a mud pit 634 through a hose 636, into drill pipe 618, and down to drill bit 626. The drilling fluid can flow out from drill bit 626 and return back to the surface through an annular area 640 between drill pipe 618 and the sides of borehole 612. The drilling fluid may then be returned to the mud pit 634, for example via pipe 637, and the fluid is filtered. The drilling fluid cools drill bit 626, as well as provides for lubrication of drill bit 626 during the drilling operation. Additionally, the drilling fluid removes the cuttings of subsurface formations 614 created by drill bit 626.

Still referring to FIG. 6, downhole tool 624 may include one to a number of different sensors 645, which monitor different downhole parameters (e.g., pressure and temperature) and generate data that is stored within one or more different storage mediums within the downhole tool 624. Alternatively, however, the data may be transmitted to a remote location (e.g., surface) and processed accordingly. The type of downhole tool 624 and the type of sensors 645 thereon may be dependent on the type of downhole parameters being measured. Such parameters may include the downhole temperature and pressure, the various characteristics of the subsurface formations (such as resistivity, radiation, density, porosity, etc.), the characteristics of the borehole (e.g., size, shape, etc.), etc.

Downhole tool 624 further includes a power source 649, such as a battery or generator. A generator could be powered either hydraulically or by the rotary power of the drill string. In this illustrative embodiment, downhole tool 624 includes a formation testing tool 650 as previously described herein, which can be powered by power source 649. In an embodiment, formation testing tool 650 is mounted on drill collar 622. Formation testing tool 650 engages the wall of borehole 612, applies a drawdown, and extracts a sample of the fluid in formation 614 or wellbore via a flow line, as previously described. In addition to drilling applications, embodiments of the present disclosure may also be deployed in a variety of other ways, including for example, slickline applications.

The methods described herein may be implemented using a system having processing circuitry necessary to determine the skin effect. The system may include a variety of deployments, such as, for example, an LWD, MWD or wireline assembly. Such circuitry may include a communications unit to facilitate interaction between the logging system and a remote location (such as the surface). A visualization unit may also be connected to communications unit to monitor data being processed; for example, an operator may intervene in the system operations based on this data. A data processing unit may convert the received data into wellbore data including, for example, skin effects. Thereafter, results may be displayed via the visualizing unit.

The system control center may also include storage/communication circuitry necessary to perform the methods described herein. In certain embodiments, that circuitry is communicably coupled to downhole sensors in order to process the received signals and/or measurements. Additionally, the circuitry on-board the logging assembly may be communicably coupled via wired or wireless connections to the surface to thereby communicate data back uphole and/or to other assembly components. In an alternate embodiment, the system control center or other circuitry necessary to perform one or more aspects of the techniques described herein may be located at a remote location away from the logging assembly, such as the surface or in a different wellbore. In other embodiments, the measurements may be communicated remotely to the system control center for processing. These and other variations will be readily apparent to those ordinarily skilled in the art having the benefit of this disclosure.

Moreover, the on-board circuitry includes at least one processor and a non-transitory and computer-readable storage, all interconnected via a system bus. Software instructions executable by the system control center for implementing the illustrative methods described herein in may be stored in local storage or some other non-transitory computer-readable medium. It will also be recognized that the positioning software instructions may also be loaded into the storage from a CD-ROM or other appropriate storage media via wired or wireless methods.

Moreover, various aspects of the disclosure may be practiced with a variety of computer-system configurations, including hand-held devices, multiprocessor systems, microprocessor-based or programmable-consumer electronics, minicomputers, mainframe computers, and the like. Any number of computer-systems and computer networks are acceptable for use with the present disclosure. The disclosure may be practiced in distributed-computing environments where tasks are performed by remote-processing devices that are linked through a communications network. In a distributed-computing environment, program modules may be located in both local and remote computer-storage media including memory storage devices. The present disclosure may therefore, be implemented in connection with various hardware, software or a combination thereof in a computer system or other processing system.

Accordingly, methods of the present disclosure provide a number of advantages. The present disclosure allows estimation of skin using an alternate method to that of conventional approaches. More often than not, reservoir engineers have a hard time nailing down skin effect. Having an alternate method such as provided herein, that relies on another measurement in the field (temperature), provides more confidence in the estimation of this important parameter. Skin is useful for testing, production analysis, and prediction. Moreover, methods of the present disclosure eliminate the need of performing a buildup that is often not conducive to productivity.

Embodiments described herein further relate to any one or more of the following paragraphs:

1. A method to determine skin effect around a wellbore, the method comprising obtaining data corresponding to wellbore characteristics, reservoir characteristics, and a first preliminary pressure drop around a wellbore due to a heating or cooling effect; inputting the data into a wellbore fluid temperature model to thereby calculate a wellbore fluid temperature profile; calibrating the calculated wellbore fluid temperature profile using a measured wellbore temperature profile; and determining a final pressure drop around the wellbore due to a heating or cooling effect using the calibrated wellbore fluid temperature profile, wherein the final pressure drop may be applied to determine the skin effect around the wellbore.

2. The method as defined in paragraph 1, further comprising inputting the data into a reservoir fluid temperature model to thereby calculate a reservoir fluid temperature profile; and calibrating the calculated reservoir fluid temperature profile using a measured reservoir fluid temperature profile, wherein the calibrated wellbore and reservoir fluid temperature profiles are used to determine the final pressure drop around the wellbore due to the heating or cooling effect.

3. The method as defined in paragraphs 1 or 2, wherein calibrating the calculated wellbore fluid temperature further comprises comparing the calculated wellbore fluid temperature profile to the measured wellbore fluid temperature profile; determining if a difference between calculated and measured wellbore fluid temperature profiles is within a threshold; and if not within the threshold, inputting a second preliminary pressure drop into the wellbore fluid temperature model.

4. The method as defined in any of paragraphs 1-3, wherein calibrating the calculated reservoir fluid temperature further comprises comparing the calculated reservoir fluid temperature profile to the measured reservoir fluid temperature profile, the measured reservoir fluid temperature profile being measured near a bottom of the wellbore; determining if a difference between the calculated and measured reservoir fluid temperature profiles is within a threshold; and if not within the threshold, inputting a second preliminary pressure drop into the wellbore and reservoir fluid temperature models.

5. The method as defined in any of paragraphs 1-4, wherein a formation test string is used to obtain the data.

6. The method as defined in any of paragraphs 1-5, further comprising deducting heat generated by the formation testing string when calculating the wellbore fluid temperature profile.

7. The method as defined in any of paragraphs 1-6, wherein a formation test string is not used to obtain the data.

8. The method as defined in any of paragraphs 1-7, further comprising performing a production or stimulation treatment analysis of the wellbore based upon the skin effect.

9. A system to determine skin effect in a wellbore, the system comprising one or more wellbore sensors communicably coupled to a processor; and a memory coupled to the processor having instructions stored therein, which when executed by the processor, cause the processor to perform operations comprising: obtaining data corresponding to wellbore characteristics, reservoir characteristics, and a first preliminary pressure drop around a wellbore due to a heating or cooling effect; inputting the data into a wellbore fluid temperature model to thereby calculate a wellbore fluid temperature profile; calibrating the calculated wellbore fluid temperature profile using a measured wellbore temperature profile; and determining a final pressure drop around the wellbore due to a heating or cooling effect using the calibrated wellbore fluid temperature profile, wherein the final pressure drop may be applied to determine the skin effect around the wellbore.

10. The system as defined in paragraph 9, further comprising inputting the data into a reservoir fluid temperature model to thereby calculate a reservoir fluid temperature profile; and calibrating the calculated reservoir fluid temperature profile using a measured reservoir fluid temperature profile, wherein the calibrated wellbore and reservoir fluid temperature profiles are used to determine the final pressure drop around the wellbore due to the heating or cooling effect.

11. The system as defined in paragraphs 9 or 10, wherein calibrating the calculated wellbore fluid temperature further comprises comparing the calculated wellbore fluid temperature profile to the measured wellbore fluid temperature profile; determining if a difference between calculated and measured wellbore fluid temperature profiles is within a threshold; and if not within the threshold, inputting a second preliminary pressure drop into the wellbore fluid temperature model.

12. The system as defined in any of paragraphs 9-11, wherein calibrating the calculated reservoir fluid temperature further comprises comparing the calculated reservoir fluid temperature profile to the measured reservoir fluid temperature profile, the measured reservoir fluid temperature profile being measured near a bottom of the wellbore; determining if a difference between the calculated and measured reservoir fluid temperature profiles is within a threshold; and if not within the threshold, inputting a second preliminary pressure drop into the wellbore and reservoir fluid temperature models.

13. The system as defined in any of paragraphs 9-12, further comprising a formation test string used to obtain the data.

14. The system as defined in any of paragraphs 9-13, further comprising deducting heat generated by the formation testing string when calculating the wellbore fluid temperature profile.

15. The system as defined in any of paragraphs 9-14, wherein a formation test string is not used to obtain the data.

16. The system as defined in any of paragraphs 9-15, further comprising performing a production or stimulation treatment analysis of the wellbore based upon the skin effect.

Moreover, the methods described herein may be embodied within a system comprising processing circuitry to implement any of the methods, or a in a non-transitory computer-readable medium comprising instructions which, when executed by at least one processor, causes the processor to perform any of the methods described herein.

The foregoing disclosure may repeat reference numerals and/or letters in the various examples. This repetition is for the purpose of simplicity and clarity and does not in itself dictate a relationship between the various embodiments and/or configurations discussed. Further, spatially relative terms, such as “beneath,” “below,” “lower,” “above,” “upper” and the like, may have been used herein for ease of description to describe one element or feature's relationship to another element(s) or feature(s) as illustrated in the figures. The spatially relative terms are intended to encompass different orientations of the apparatus in use or operation in addition to the orientation depicted in the figures. For example, if the apparatus in the figures is turned over, elements described as being “below” or “beneath” other elements or features would then be oriented “above” the other elements or features. Thus, the exemplary term “below” can encompass both an orientation of above and below. The apparatus may be otherwise oriented (rotated 90 degrees or at other orientations) and the spatially relative descriptors used herein may likewise be interpreted accordingly.

Although various embodiments and methods have been shown and described, the disclosure is not limited to such embodiments and methods and will be understood to include all modifications and variations as would be apparent to one skilled in the art. Therefore, it should be understood that the disclosure is not intended to be limited to the particular forms disclosed. Rather, the intention is to cover all modifications, equivalents and alternatives falling within the spirit and scope of the disclosure as defined by the appended claims. 

1. A method to determine skin effect around a wellbore, the method comprising: obtaining data corresponding to wellbore characteristics, reservoir characteristics, and a first preliminary pressure drop around a wellbore due to a heating or cooling effect; inputting the data into a wellbore fluid temperature model to thereby calculate a wellbore fluid temperature profile; calibrating the calculated wellbore fluid temperature profile using a measured wellbore temperature profile; and determining a final pressure drop around the wellbore due to a heating or cooling effect using the calibrated wellbore fluid temperature profile, wherein the final pressure drop may be applied to determine the skin effect around the wellbore.
 2. The method as defined in claim 1, further comprising: inputting the data into a reservoir fluid temperature model to thereby calculate a reservoir fluid temperature profile; and calibrating the calculated reservoir fluid temperature profile using a measured reservoir fluid temperature profile, wherein the calibrated wellbore and reservoir fluid temperature profiles are used to determine the final pressure drop around the wellbore due to the heating or cooling effect.
 3. The method as defined in claim 1, wherein calibrating the calculated wellbore fluid temperature further comprises: comparing the calculated wellbore fluid temperature profile to the measured wellbore fluid temperature profile; determining if a difference between calculated and measured wellbore fluid temperature profiles is within a threshold; and if not within the threshold, inputting a second preliminary pressure drop into the wellbore fluid temperature model.
 4. The method as defined in claim 2, wherein calibrating the calculated reservoir fluid temperature further comprises: comparing the calculated reservoir fluid temperature profile to the measured reservoir fluid temperature profile, the measured reservoir fluid temperature profile being measured near a bottom of the wellbore; determining if a difference between the calculated and measured reservoir fluid temperature profiles is within a threshold; and if not within the threshold, inputting a second preliminary pressure drop into the wellbore and reservoir fluid temperature models.
 5. The method as defined in claim 1, wherein a formation test string is used to obtain the data.
 6. The method as defined in claim 5, further comprising deducting heat generated by the formation testing string when calculating the wellbore fluid temperature profile.
 7. The method as defined in claim 2, wherein a formation test string is not used to obtain the data.
 8. The method as defined in claim 1, further comprising performing a production or stimulation treatment analysis of the wellbore based upon the skin effect.
 9. A system to determine skin effect in a wellbore, the system comprising: one or more wellbore sensors communicably coupled to a processor; and a memory coupled to the processor having instructions stored therein, which when executed by the processor, cause the processor to perform operations comprising: obtaining data corresponding to wellbore characteristics, reservoir characteristics, and a first preliminary pressure drop around a wellbore due to a heating or cooling effect; inputting the data into a wellbore fluid temperature model to thereby calculate a wellbore fluid temperature profile; calibrating the calculated wellbore fluid temperature profile using a measured wellbore temperature profile; and determining a final pressure drop around the wellbore due to a heating or cooling effect using the calibrated wellbore fluid temperature profile, wherein the final pressure drop may be applied to determine the skin effect around the wellbore.
 10. The system as defined in claim 9, further comprising: inputting the data into a reservoir fluid temperature model to thereby calculate a reservoir fluid temperature profile; and calibrating the calculated reservoir fluid temperature profile using a measured reservoir fluid temperature profile, wherein the calibrated wellbore and reservoir fluid temperature profiles are used to determine the final pressure drop around the wellbore due to the heating or cooling effect.
 11. The system as defined in claim 9, wherein calibrating the calculated wellbore fluid temperature further comprises: comparing the calculated wellbore fluid temperature profile to the measured wellbore fluid temperature profile; determining if a difference between calculated and measured wellbore fluid temperature profiles is within a threshold; and if not within the threshold, inputting a second preliminary pressure drop into the wellbore fluid temperature model.
 12. The system as defined in claim 10, wherein calibrating the calculated reservoir fluid temperature further comprises: comparing the calculated reservoir fluid temperature profile to the measured reservoir fluid temperature profile, the measured reservoir fluid temperature profile being measured near a bottom of the wellbore; determining if a difference between the calculated and measured reservoir fluid temperature profiles is within a threshold; and if not within the threshold, inputting a second preliminary pressure drop into the wellbore and reservoir fluid temperature models.
 13. The system as defined in claim 9, further comprising a formation test string used to obtain the data.
 14. The system as defined in claim 13, further comprising deducting heat generated by the formation testing string when calculating the wellbore fluid temperature profile.
 15. The system as defined in claim 10, wherein a formation test string is not used to obtain the data.
 16. The system as defined in claim 9, further comprising performing a production or stimulation treatment analysis of the wellbore based upon the skin effect.
 17. A non-transitory computer-readable medium comprising instructions which, when executed by at least one processor, causes the processor to perform the method of claim
 1. 